Odense Q W vs ASA Aarhus W prediction
KvindeligaRound 12
Odense Q W11:30
Sun 25 Oct
Prediction T-24h
ASA Aarhus WMost likelyASA Aarhus W win · 49%
Prediction
24%1Odense Q W
27%XDraw
49%2ASA Aarhus W
These are calibrated probabilities. See how closely they've matched real outcomes
Stale predictionPrediction as of 13 Oct 2026Predictions for this league are paused — this is the last one we made, not a live call.
Odds comparison
| Bookmaker | Odense Q W | ASA Aarhus W |
|---|
Bookmaker names shown for reference only. No affiliate links.
Stake sizer
This prediction is stale (paused league or not refreshed), so we size nothing on it.
Hypothetical sizing in currency-neutral units, not betting advice. Predictions are probabilities, not guarantees. 18+.
Match context
Strength-adjusted form
Odense Q W
- L0-3FHW
- W1-0AW
- D1-1AAW
- L0-4BW
- L0-4FHW
↑ stronger · = even · ↓ weaker opponent
ASA Aarhus W
- W1-0MW
- L0-3BW
- D1-1OQW
- W3-1KW
- L0-1FCW
↑ stronger · = even · ↓ weaker opponent
Injuries & absences
Odense Q W
No reported absences.
ASA Aarhus W
No reported absences.
Head to head
Odense Q W 0Draws 2ASA Aarhus W 1
- AAW 1-1 OQW
- AAW 2-2 OQW
- OQW 1-3 AAW
Recent form
Recent form — context only, not a tip.
Odense Q W
Goals
- Scored / game
- 0.6last 10
- Conceded / game
- 2.1last 10
- Clean sheets
- 2 / 10
- BTTS
- 3 / 10
- Over 2.5
- 6 / 10
ASA Aarhus W
Goals
- Scored / game
- 1.2last 10
- Conceded / game
- 1.9last 10
- Clean sheets
- 1 / 10
- BTTS
- 6 / 10
- Over 2.5
- 7 / 10
Line movement
Odense Q W—
No line movement recorded yet
Draw—
No line movement recorded yet
ASA Aarhus W—
No line movement recorded yet
Under the hood
How the model sees this match — the drivers and, after full-time, how the prediction scored.
Why this prediction
ExplanationAI · grounded
The model leans toward a ASA Aarhus W result here, shaped mainly by Expected goals (home) and Expected goals (away). The probabilities come from the model — the prose only narrates them.
The AI writes the prose. It never produces or adjusts a probability — those come only from the model.
How we make these predictionsTop model factors
Expected goals (home)0.88Expected goals (away)1.37Goal correlation0.02
The driver chips attribute the gradient-boosted component of an ensemble whose headline is additionally anchored to the market where a consensus exists — they explain that part of the number, not all of it.